Knowledge transfer in pair programming: An in-depth analysis

Whilst knowledge transfer is one of the most widely-claimed benefits of pair programming, little is known about how knowledge transfer is achieved in this setting. This is particularly pertinent for novice−expert constellations, but knowledge transfer takes place to some degree in all constellations. We ask “what does it take to be a good “expert” and how can a “novice” best learn from a more experienced developer?”. An in-depth investigation of video and audio excerpts of professional pair programming sessions using Interaction Analysis reveals: six teaching strategies, ranging from “giving direct instructions” to “subtle hints”; and challenges and benefits for both partners. These strategies are instantiations of some but not all teaching methods promoted in cognitive apprenticeship; novice articulation, reflection and exploration are not seen in the data. The context of pair programming influences the strategies, challenges and benefits, in particular the roles of driver and navigator and agile prioritisation which considers business value rather than educational progression. Utilising these strategies more widely and recognizing the challenges and benefits for both partners will help developers to maximise the benefits from pairing sessions.     

Learning fuzzy controllers in mobile robotics with embedded preprocessing

The automatic design of controllers for mobile robots usually requires two stages. In the first stage, sensorial data are preprocessed or transformed into high level and meaningful values of variables which are usually defined from expert knowledge. In the second stage, a machine learning technique is applied to obtain a controller that maps these high level variables to the control commands that are actually sent to the robot. This paper describes an algorithm that is able to embed the preprocessing stage into the learning stage in order to get controllers directly starting from sensorial raw data with no expert knowledge involved. Due to the high dimensionality of the sensorial data, this approach uses Quantified Fuzzy Rules (QFRs), that are able to transform low-level input variables into high-level input variables, reducing the dimensionality through summarization. The proposed learning algorithm, called Iterative Quantified Fuzzy Rule Learning (IQFRL), is based on genetic programming. IQFRL is able to learn rules with different structures, and can manage linguistic variables with multiple granularities. The algorithm has been tested with the implementation of the wall-following behavior both in several realistic simulated environments with different complexity and on a Pioneer 3-AT robot in two real environments. Results have been compared with several well-known learning algorithms combined with different data preprocessing techniques, showing that IQFRL exhibits a better and statistically significant performance. Moreover, three real world applications for which IQFRL plays a central role are also presented: path and object tracking with static and moving obstacles avoidance.     

A proposed expert system for word sense disambiguation: deductive ambiguity resolution based on data mining and forward chaining

One of the major issues in the process of machine translation is the problem of choosing the proper translation for a multi‐sense word referred to as word sense disambiguation (WSD). Two commonly used approaches to this problem are statistical and example‐based methods. In statistical methods, ambiguity resolution is mostly carried out by making use of some statistics extracted from previously translated documents or dual corpora of source and target languages. Example‐based methods follow a similar approach as they also make use of bilingual corpora. However, they perform the task of matching at run‐time (i.e. online matching). In this paper, by looking at the WSD problem from a different viewpoint, we propose a system, which consists of two main parts. The first part includes a data mining algorithm, which runs offline and extracts some useful knowledge about the co‐occurrences of the words. In this algorithm, each sentence is imagined as a transaction in Market Basket Data Analysis problem, and the words included in a sentence play the role of purchased items. The second part of the system is an expert system whose knowledge base consists of the set of association rules generated by the first part. Moreover, in order to deduce the correct senses of the words, we introduce an efficient algorithm based on forward chaining in order to be used in the inference engine of the proposed expert system. The encouraging performance of the system in terms of precision and recall as well as its efficiency will be analysed and discussed through a set of experiments.     

Dynamic facility layout problem in footwear industry

Dynamic facility layout problem (DFLP) deals with the arrangement of machines in a site as to minimize the sum of materials handling and re-layout costs by considering multi periods. The DFLP studies in the literature provide several different algorithms and utilize the well known test problems to assess their performance. However, real life applications are overlooked. The industries such as footwear and clothing are prone to seasonal demand changes. Therefore, time horizons and layout/re-layout of the machines within the facility should be studied carefully. This study considers a footwear facility and several scenarios are generated by using the real life data. A clonal selection based algorithm is proposed to solve the real life DFLP. The performance of the algorithm, further the effect of time periods on solution quality and applicability of the results are tested and promising results are obtained.     

Decision evaluation process in end-of-life systems management

In manufacturing sectors, firms are paying an increasing attention to sustainability concept with regard to their end-of-life products in order to respect environmental norms and satisfy the consumer sensitivity. This practise allows creating value by reintroducing dismantling and recovering parts and/or materials of end-of-life products into manufacturing process, or into maintenance process. Thus, deconstruction processes are developed in order to examine all activities addressing the end of life (EOL) systems to ensure its disposal according to environmental constraints when seeking an economic optimum. In this context, one of the first tasks to perform is to repatriate the EOL systems at lowest cost considering geographical optimization of treatment centers. Considering this point, the present paper proposes an evaluation and optimization approach for the withdrawal location process in the field of aircraft dismantling. Given the multitude and heterogeneity of characteristics to be taken into account, we propose to consider dismantling site location problem as multi-criteria/multi-objectives decision making problem and solve it using a new AHP-BOCR approach based on qualitative and quantitative evaluations. A bipolar structuring framework is considered to distinguish positive and negative aspects in the elicitation/evaluation process to avoid compensation and satisficing game theory is used as suitable mathematical tool for recommendation process. An experimental study is carried out to show the usefulness of the framework.     

The influence of thermal residual stresses and thermal generated dislocation on the mechanical response of particulate-reinforced metal matrix nanocomposites

Due to thermal expansion mismatch between reinforcing particles and matrix, thermal induced dislocations are generated in metal matrix nanocomposites (MMNCs) during cooling down from the processing temperature. These dislocations have been identified as an important strengthening mechanism in particulate-reinforced MMNCs. In this study, the development of thermal residual stresses and thermal induced dislocations in MMNCs are predicted using discrete dislocation simulation, assuming the whole material is under uniform temperature change. Shear deformation is applied after the composites are cooled down to room temperature and the influence of thermal residual stresses and thermal generated dislocation on the overall response of particulate-reinforced MMNCs are investigated. The results show that the thermal residual stresses are high enough to generate dislocations and the dislocation density is higher in the interfacial region than the rest of the matrix. The predicted mechanical behavior of the MMNCs matches the experimental results better when thermal residual stresses are included in the simulations.     

Dielectric response and energy storage efficiency of low content TiO2-polymer matrix nanocomposites

TiO₂/epoxy nanocomposites were prepared at different filler concentrations varying from 3 to 12 phr (parts per hundred resin per weight). The dispersion of TiO₂ was examined by Scanning Electron Microscopy and proved to be adequate. Differential Scanning Calorimetry was implemented to determine the glass to rubber transition temperature of the polymer matrix. The dielectric analysis was performed via Broadband Dielectric Spectroscopy in a wide frequency and temperature range. Five different mechanisms were observed in the spectra of the examined composites which are identified, in terms of increasing temperature at constant frequency, as γ, β, Intermediate Dipolar Effect (IDE), α and Interfacial Polarization (IP) relaxation modes. The activation energies of all relaxation modes were calculated. Finally, the dielectric response of the TiO₂ nanocomposites compared to that of the TiO₂ microcomposites reveals that the former exhibit significantly higher energy storage efficiency even at lower TiO₂ concentration than the corresponding of the microcomposites.     

Performances at high temperature of RC bridge decks strengthened with EBR-FRP

Fiber reinforced polymer (FRP) can be successfully used to externally strengthen reinforced concrete (RC) bridges where fire is not a primary concern. Nevertheless, common maintenance activity on a bridge deck, such as the laying of bituminous paving, can easily lead the FRP to temperatures higher than the glass transition temperature, T_g. Exceeding T_g does not necessarily imply a drastic reduction in strength and stiffness of the reinforcement. Nevertheless, the softening of the resin implies a drastic reduction in its adhesion properties. Therefore, the efficiency of the strengthening system for existing structures, which mainly depends on the effectiveness of the bond between FRP and concrete, is significantly affected by temperature.The relationships suggested by Italian and American codes in order to evaluate the limit strain for FRP debonding at normal temperature are modified to take into account the effect of high temperature. Then, performances at high temperature of RC bridge decks strengthened with externally bonded FRP plates (EBR) are investigated by considering thermal fields in the structural members which are different from the normal ones. Both fire and the laying of bituminous paving on the decks are considered. In addition, the thicknesses of the slabs and the protective layer are varied to assess their influence on the thermal field in the slabs. The results are discussed with reference to both ultimate and serviceability limit states.     

Structural performance of ballastless track slabs reinforced with BFRP and SFCB

Because of the inductive impedance caused by steel meshes in traditional reinforced ballastless track slabs, the electrical properties, primarily the rail resistance and inductance, of jointless track circuits are affected by electromagnetic induction between the slabs and the electric current in the rail. This problem results in poor transmission performance throughout the track circuit. Insulating sleeves or cards between the steel meshes have been used to improve the insulation capability of steel meshes in slabs; however, they reduce the bonding performance between the steel bars and concrete. Because of the good insulation properties of fiber-reinforced polymer composite bars (FRPs) and steel-fiber reinforced polymer composite bars (SFCBs), these composite materials have shown potential to overcome this insulation problem. However, the structural performance of the ballastless track slabs reinforced by basalt fiber reinforced polymer composite bars (BFRPs) and SFCBs, which play a key role in the structure and transportation safety, needs to be investigated. In this paper, six ballastless track slabs reinforced with BFRPs, SFCBs, and steel bars were constructed and tested. The following results were obtained. (1) Shear failures were observed for all slabs, both the BFRP and SFCB slabs meet the load level requirements, and SFCBs reinforcements have higher strength utilization compared with BFRPs reinforcements. (2) The bond-quality of SFCBs and BFRPs reinforcements proved slightly poorer than that of the steel bars. Because of the good corrosion resistance of the FRP, the maximum crack width limits can be slightly larger than that of the RC slabs. (3) Bischoff’s equation was initially used to calculate the deflection of partially prestressed concrete slabs under service loads. The results demonstrated a good agreement between the theoretical and experimental analysis. (4) Considering the tensile stiffness, the modified ACI equation was used to calculate the slabs’ crack width and the theoretical and experimental results showed a good agreement.     

Cylindrical conformal single-patch microstrip antennas based on three dimensional woven glass fiber/epoxy resin composites

Three dimensional integrated microstrip antenna (3DIMA) can carry the designed load while functioning as an antenna. In this study, the cylindrical conformal single-patch 3DIMAs with various curvatures were designed, simulated, fabricated and tested experimentally using a 3D orthogonal woven glass preform/epoxy resin composite system. The electromagnetic performances of the cylindrical microstrip antennas were analyzed. The simulated and tested results matched well and the return losses of the cylindrical conformal 3DIMAs with radii of curvatures of 60, 45 and 25 mm were less than −10 dB while resonant frequencies and their gain values were significantly influenced by the radius of curvature and the feeding direction. The 3DIMAs with the curvature perpendicular to the feeding directions showed more stable resonant frequencies and larger gain values than those of 3DIMAs with the curvature along their feeding directions.